Radiographic imaging such as x-ray imaging has been used for years in medical applications and for non-destructive testing.
Normally, an x-ray imaging system includes an x-ray source and an x-ray detector system. The x-ray source emits x-rays that pass through a subject or object to be imaged and are then registered by the x-ray detector system. Since some materials absorb a larger fraction of the x-rays than others, an image is formed of the subject or object.
It may be useful to begin with a brief overview of an illustrative overall x-ray imaging system, with reference to FIG. 1. In this non-limiting example, the x-ray imaging system 100 basically comprises an x-ray source 10, an x-ray detector system 20 and an associated image processing device 30. In general, the x-ray detector system 20 is configured for registering radiation from the x-ray source 10 that may have been focused by optional x-ray optics and passed an object or subject or part thereof. The x-ray detector system 20 is connectable to the image processing device 30 via suitable analog processing and read-out electronics (which may be integrated in the x-ray detector system 20) to enable image processing and/or image reconstruction by the image processing device 30.
As illustrated in FIG. 2, another example of an x-ray imaging system 100 comprises an x-ray source 10, which emits x-rays; an x-ray detector system 20, which detects the x-rays after they have passed through the object; analog processing circuitry 25, which processes the raw electrical signal from the detector and digitizes it; digital processing circuitry 40 which may carry out further processing operations on the measured data such as applying corrections, storing it temporarily, or filtering; and a computer 50 which stores the processed data and may perform further post-processing and/or image reconstruction.
The overall detector may be regarded as the x-ray detector system 20, or the x-ray detector system 20 combined with the associated analog processing circuitry 25.
The digital part including the digital processing circuitry 40 and/or the computer 50 may be regarded as a digital image processing system 30, which performs image reconstruction based on the image data from the x-ray detector. The image processing system 30 may thus be seen as the computer 50, or alternatively the combined system of the digital processing circuitry 40 and the computer 50, or possibly the digital processing circuitry 40 by itself if the digital processing circuitry is further specialized also for image processing and/or reconstruction.
An example of a commonly used x-ray imaging system is a Computed Tomography (CT) system. FIG. 3 is a schematic diagram illustrating an example of a CT system. In the example of FIG. 3, the CT system may include an x-ray source that produces a fan- or cone-beam of x-rays and an opposing x-ray detector system for registering the fraction of x-rays that are transmitted through a patient or object. The x-ray source and detector system are normally mounted in a gantry that rotates around the imaged object. Accordingly, the x-ray source and the x-ray detector system illustrated in FIG. 3 may be arranged as part of a CT system, e.g. mountable in a CT gantry. The overall CT system may also include appropriate controllers and management systems.
FIG. 4 is a schematic diagram of an x-ray detector according to an exemplary embodiment. In this example there is shown a schematic view of an x-ray detector and x-ray source emitting x-rays. For example, the elements of the detector may be pointing back to the source, and they are preferably arranged in a slightly curved overall configuration. The dimensions and segmentation of the detector array affect the imaging capabilities of the x-ray imaging system. The direction of the incident x-rays is referred to as the y-direction. A plurality of detector pixels in the direction of the rotational axis of the gantry (referred as z-direction) enables multi-slice image acquisition. A plurality of detector pixels in the angular direction (referred as x-direction) enables measurement of multiple projections in the same plane simultaneously and this is applied in fan/cone-beam CT. Most conventional detectors have detector pixels in both the slice (z) and angular (x) directions.
Modern x-ray detectors normally convert the incident x-rays into electrons, typically through photo absorption and/or Compton interaction, and the resulting electrons create secondary visible light which in turn is detected by a photo-sensitive material. Other detectors are based on semiconductors that convert x-rays directly into electron-hole pairs that are collected by drifting the charge carriers in an applied electric field.
Most x-ray detectors used for medical imaging today are energy integrating, meaning the output signal is the sum of the energies of the photons that interacted during the measurement period. The contribution from each detected photon to the signal is thus proportional to the energy of the photon.
Photon-counting detectors have also emerged as a feasible alternative in some applications; currently photon-counting detectors are commercially available in, for example, mammography. Many photon-counting detectors are spectral (energy resolving), meaning that they can categorize detected photons based on the energy that is deposited in the detector material when the photon interacts. The energy categorization is performed using energy bins that are defined by programmable energy thresholds. The energy information can be used to obtain additional information about the composition of the object through which the photons have traversed. This additional information can in turn be used to increase the image quality and/or to decrease the radiation dose.
Compared to energy-integrating x-ray detector systems, photon-counting x-ray detector systems have the following advantages: the energy thresholds can be used to remove electronic noise that for energy-integrating detectors is included in the measured signal; the energy information can be used to perform so-called material basis decomposition, by which different materials and/or components in the examined subject can be identified and quantified (R. E. Alvarez, Medical Physics 38(5). 2324-2334, 2011); the detector has no afterglow (the detector produces signal output for a short time after the input signal has stopped) which increases the angular resolution; also, higher spatial resolution can be achieved by having a smaller pixel size. Materials for photon-counting x-ray detectors include cadmium telluride (CdTe), cadmium zinc telluride (CZT) and silicon (Si).
U.S. Pat. No. 8,183,535 discloses an example of a photon-counting edge-on x-ray detector. In this patent, there are multiple semiconductor detector modules arranged together to form an overall detector area, where each semiconductor detector module comprises an x-ray sensor oriented edge-on to incoming x-rays and connected to integrated circuitry for registration of x-rays interacting in the x-ray sensor.
The semiconductor detector modules are normally tiled together to form a full detector of almost arbitrary size with almost perfect geometrical efficiency.
FIG. 5 is a schematic diagram illustrating an example of a semiconductor detector module. This is an example of a semiconductor detector module with the sensor part split into detector elements, where each detector element is normally based on a diode having a charge collecting electrode as a key component. In the example of FIG. 5, the semiconductor sensor part is also split into so-called depth segments in the depth direction, assuming the x-rays enter through the edge.
Normally, a detector element is an individual x-ray sensitive sub-element of the detector. In general, the photon interaction takes place in a detector element and the thus generated charge is collected by the corresponding electrode of the detector element.
Depending on the detector topology, a detector element may correspond to a pixel, especially when the detector is a flat-panel detector. However, a depth-segmented detector may be regarded as having a number of detector strips, each strip having a number of depth segments. For such a depth-segmented detector, each depth segment may be regarded as an individual detector element, especially if each of the depth segments is associated with its own individual charge collecting electrode. The detector strips of a depth-segmented detector normally correspond to the pixels of an ordinary flat-panel detector.
The data output from a photon-counting spectral detector generally comprises the number of photons detected within an energy bin (pulse-heights between two thresholds), or the number of photons detected above an energy threshold. The photon-count data can be used to estimate the material compositions of the imaged object, a process commonly referred to as basis material decomposition. This can be done either in projection domain: the material thicknesses are estimated for each pixel individually and an image is formed for each basis material; or in the image domain: an image is formed for each energy bin, and the material estimation is performed using the different bin images.
Object collimators, also referred to as scatter rejection grids or anti-scatter grids, are commonly used in modern CT systems. Typically, they are embodied both in the angular (x) and the slice (z) directions with stacks of lamellas made by heavy metals, e.g., tungsten or molybdenum, to form walls of collimator cells, as illustrated in FIG. 6.
These collimator cells commonly hold a cell-to-pixel relationship to the detector pixels below for a better suppression of scattered radiation, as illustrated in FIG. 7. Reference can be made, e.g. to U.S. Pat. No. 9,583,228 B2, U.S. Pat. No. 8,831,181 B2, U.S. Pat. No. 7,362,849 B2. Aligning the collimator lamellas to the focus of the x-ray source in both x and z directions is a challenge, especially for densely packed detector pixels, e.g. referring to US 2013/0168567 A1.
Misalignment of the detector, the anti-scatter grid and the source leads to: errors in the geometric parameters of the image acquisition (the position at which each measurement is performed); and shadowing of the detector, which in turn can lead to loss of photons and changes of the spectral response of the detector.
Many methods have been developed for geometric calibration, i.e. estimation of the geometric parameters of the image acquisition, of CT imaging systems:
US 2014/0211925, U.S. Pat. No. 8,622,615 and US 2014/0153694 relate to geometric calibration for flat-panel detectors using a calibration phantom or device. The devices are not an integral part of the detector but placed in between the source and the detector.
U.S. Pat. No. 6,370,218, describes an invention in which the penumbra (partially illuminated region) of the x-ray illumination field is measured using a multi-slice x-ray detector to determine the position of the x-ray tube focal spot.
WO 2010/093314 mentions obtaining measurement information from an edge-on x-ray detector having depth segments and measuring the degree of shadowing using the ratio of the number of detected x-ray counts in the different depth segments.
U.S. Pat. No. 5,131,021 relates to an invention where a set of x-ray attenuating masks are placed on pixels outside of the imaged object. The position of the x-ray source in the axial (z) direction is then estimated based on ratios of the measured signal in pixels with different masks.
U.S. Pat. No. 8,262,128, a method is described for determining the location of the focal spot by having a set of anti-scatter lamella pointing towards a point other than the source location. The deliberately misaligned anti-scatter lamella cause shadowing on the detector pixels located next to the lamella and a movement of the source leads to a change of measured x-ray intensity which then can be used to estimate the source location.
Multi-pixel matched collimators (the collimator cells are matched to several detector pixels) has been suggested for single photon emission computed tomography (SPECT) system to achieve better detection efficiency. Reference can be made, e.g. to WO 2016162962 A1, WO 2011093127 A1, and A. Suzuki, et al., Physics in Medicine and Biology 58.7 (2013): 2199th. However, multi-pixel matched collimators are generally not used for CT. An example of a multi-pixel matched collimator is illustrated in FIG. 12.
There are three types of misalignments that can lead to shadowing of the detector (i.e., part of the detector cannot be illuminated by x rays) from the object collimator. The first type is misalignment of the x-ray source (either in x- or z-direction) in which case collimator lamellas will be in the path of incident x-ray beams and lead to different active cross-sections along the detector depth, as illustrated in FIG. 8. The second type is misalignment of the detector (either in x- or z-direction), which will lead to the same situation as for misalignment of the x-ray source, as illustrated in FIG. 9. The third type is misalignment of the collimator lamella, which will always result in a fixed amount of inactive detector area along the detector depth, as illustrated in FIG. 10.
Shadowing from either misalignment of the source or the collimator, leads to loss of counts in shadowed pixels. Shadowing caused by source misalignment also results in different active cross-sections of detector material at different depths in the detector. Since the detector has different spectral response at different depths, this implies that the spectral response of each detector pixel will depend on the degree of shadowing. This effect will here be referred to as the non-linear spectral effect. Different spectral response results in a difficult normalization problem; the relative gain of each pixel (the output signal as a function of input signal) depends on the shape of the incoming x-ray spectrum. It is therefore difficult to remove pixel differences by, for example, normalizing the output signal by a single correction factor determined from a single reference measurement, e.g. an air scan (so called flat-fielding). If pixels with different spectral responses are left uncorrected, there is a risk that the reconstructed images have ring artifacts (rings of brighter or darker values due to higher or lower gain of a detector pixel compared its neighboring pixels).
Energy integrating detectors cannot correct for the different spectral responses even if the degree of shadowing in pixels can be properly known since there is no spectral information available. The pixels on an energy integrating detector must therefore have close to identical spectral response to cope with the non-linear spectral effect. This can, for example, be obtained by blocking the regions that risk shadowing (i.e. the edges of the pixel) with a highly attenuating material (illustrated in FIG. 11), referring to US 2016/0025867 A1, US 2013/0121475 A1, or by tilting collimator lamellas with respect to the detector array with a predetermined angle (could be more than 1° C.), referring to US 2013/0121475 A1, or by adjusting the heights of collimator lamellas to guarantee that the shadowing effect is smaller than a threshold (e.g., 5% reduction of detection efficiency), referring to CN 1596829 A.
For photon-counting spectral detectors, on the other hand, it is not necessary to have identical spectral response if images are formed using material basis decomposition in the projection domain. Any spectral differences that are the same during system calibration as during image acquisition scans (e.g. static misalignments) can be removed by performing material basis decomposition with a forward model[6] that accurately captures pixel-dependent detector responses. The forward model can for example be obtained from a material calibration during the system calibration (R. E. Alvarez, Medical Physics 38(5). 2324-2334, 2011).
However, for dynamic misalignment, caused by e.g. mechanical movements during scans, there is no prior knowledge from the system calibration and therefore it cannot be corrected with calibration data. Although a source monitor can be used to monitor the position of the x-ray source for further correction, it is difficult to achieve a high degree of accuracy. For energy-integrating detectors, the effects of dynamic misalignment are mitigated using, for example, the method suggested in US 2016/0025867 A1, which requires an extra grid between the object collimator and the detector to provide more shielding and thus guarantee uniform active area among different detector pixels also if for example the source has moved during a scan.
An illustration is shown in FIG. 11 where pixel A and pixel B have the same active area even though there are misalignments both of collimator lamella and the source. However, the method implies a big sacrifice of geometric efficiency of the detector, which can be seen from FIG. 11 (the x-rays that are blocked by the extra grid are lost), and this sacrifice will be larger if the method is used for photon-counting detectors due to their smaller pixel sizes.